Data Engineer

Prasanz; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Prasanz is seeking a Data Engineer to design, deploy, and monitor data pipelines in Hyderabad. You will orchestrate ETL/ELT workflows, manage data warehouse schemas, and ensure access to clean transactional data for engineering teams.

You will build pipelines with Python, Spark, SQL, and orchestrate workloads using Airflow and dbt, while leveraging Snowflake, Redshift or BigQuery in a cloud environment. 4+ years of experience is expected.

Qualifications

• 4+ years in data engineering or data platform roles.
• Strong SQL, indexing, and warehouse partitioning.
• Experience building pipelines with Spark, Airflow, and dbt.

Responsibilities

• Design and scale distributed data pipelines using Python, Spark, and SQL.
• Model data warehouse structures in Snowflake with star schemas.
• Orchestrate pipelines with Airflow and transform data with dbt.
• Ingest structured, semi-structured, and streaming data payloads.
• Implement data validation layers and monitor schema changes.

Skills

SQL design

Python

Apache Spark

Apache Airflow

dbt

Cloud data warehouses

Tools

Snowflake

AWS Redshift

Google BigQuery

Job description

Full-Time Hyderabad, India (Offshore)

Primary Technology Stack

Python Apache Spark Snowflake SQL Apache Airflow dbt AWS

About The Role

We are hiring a Data Engineer to design, deploy, and monitor our data pipeline systems. You will orchestrate reliable ETL/ELT workflows, manage data warehouse schemas, and ensure engineering teams have access to clean transactional data.

Key Responsibilities

• Design and scale distributed data pipelines using Python, Apache Spark, and SQL.
• Model data warehouse structures in Snowflake, maintaining star-schemas and analytical indices.
• Orchestrate complex pipeline dependencies using Apache Airflow and transform data using dbt.
• Build pipelines to ingest structured, semi-structured, and streaming payloads.
• Implement data validation layers, monitoring schema changes and database errors.

Required Qualifications

• 4+ years of experience in a dedicated Data Engineering or Data Platform role.
• Mastery of SQL query design, database optimization, indexing, and warehouse partitioning.
• Hands-on experience building pipelines with Apache Spark, Airflow, and dbt.
• Solid experience working with cloud data warehouses (Snowflake, AWS Redshift, or Google BigQuery).
• Experience writing clean, modular Python pipelines following software engineering standards.